Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method of ranking a version of an open source software program, the method comprising: querying, by an information handling system, a data source to retrieve electronic data describing the version of the open source software program; generating, by the information handling system, an open source stability index based on the electronic data describing the version of the open source software program, wherein the open source stability changes based on a number of issues closed and based on a number of new issues raised in the version of the open source software program; performing, by the information handling system, a time trend analysis based on the electronic data describing the version of the open source software program, wherein the time trend analysis includes determining how often in time the version of the open source software program was updated and determining how much time was needed to get a stable version of the open source software program based on no issues remaining in the version of the open source software program; generating, by the information handling system, an open source security index based on the electronic data describing the version of the open source software program; and generating, by the information handling system, the ranking of the version of the open source software program based on the open source stability index and on the open source security index.
2. The method of claim 1 , further comprising assigning a numerical value to the open source stability index.
The invention relates to assessing the stability of open-source software projects. Many open-source projects lack standardized metrics for evaluating their long-term viability, making it difficult for developers and organizations to assess risks before adoption. This invention addresses this problem by providing a method to quantify the stability of open-source projects using a stability index. The method involves analyzing multiple factors that influence project stability, such as code quality, community activity, and maintenance frequency. These factors are evaluated using predefined criteria, and a stability score is generated based on the analysis. The score is then assigned a numerical value, allowing for easy comparison between different projects. This numerical value can be used to rank projects or set thresholds for adoption decisions. The method may also include tracking changes in the stability index over time to monitor trends and predict potential risks. By providing a quantifiable measure of stability, the invention helps users make informed decisions about which open-source projects to rely on, reducing the risk of adopting unstable or poorly maintained software. The numerical value assigned to the stability index enables clear, objective comparisons, improving transparency and trust in open-source software evaluations.
3. The method of claim 1 , further comprising assigning a numerical value to the open source security index.
The invention relates to assessing and quantifying the security risks associated with open-source software components. The problem addressed is the lack of standardized metrics to evaluate the security posture of open-source projects, making it difficult for developers to make informed decisions about software dependencies. The solution involves generating an open-source security index that evaluates multiple security-related factors, such as vulnerability history, patch response time, and code quality. This index provides a quantifiable measure of risk, enabling developers to compare and prioritize open-source components based on their security profiles. The method further includes assigning a numerical value to the open-source security index, allowing for objective comparisons and integration into software development workflows. By standardizing security assessments, the invention helps organizations mitigate risks associated with open-source dependencies and improve overall software security. The approach may also incorporate historical data, community activity, and compliance with security best practices to refine the index. This numerical valuation facilitates automated decision-making in software supply chain management, ensuring that high-risk components are flagged or excluded from projects. The invention aims to enhance transparency and trust in open-source software by providing actionable insights into security risks.
4. The method of claim 1 , further comprising keyword matching the electronic data to the version of the open source software program.
The invention relates to systems and methods for managing and analyzing electronic data, particularly in the context of open source software programs. The core problem addressed is the need to efficiently and accurately identify and process electronic data that is associated with specific versions of open source software programs. This is important for compliance, auditing, and security purposes, where it is critical to determine whether electronic data matches or is derived from a particular version of an open source software program. The method involves analyzing electronic data to determine its relationship with an open source software program. This includes comparing the electronic data to the program's source code, binaries, or other artifacts to establish a connection. The method further includes keyword matching the electronic data to the version of the open source software program. This step involves identifying specific keywords, patterns, or markers within the electronic data that correspond to known features, functions, or identifiers of the software program's version. By performing this matching, the system can confirm whether the electronic data is associated with the intended version of the software, ensuring accuracy in tracking and compliance. The method may also include additional steps such as generating reports, flagging discrepancies, or integrating with other software management tools to provide a comprehensive solution for managing open source software dependencies and licenses. The overall goal is to streamline the process of verifying and validating electronic data against open source software programs, reducing manual effort and improving reliability.
5. The method of claim 1 , further comprising performing a software sentiment analysis based on the electronic data describing the version of the open source software program.
6. The method of claim 5 , further comprising generating the ranking of the version of the open source software program based on the software sentiment analysis.
This invention relates to software analysis, specifically ranking versions of open-source software programs based on sentiment analysis. The problem addressed is the difficulty in evaluating the quality and reliability of different versions of open-source software, which often lack centralized quality metrics. The solution involves analyzing user feedback, developer discussions, and other textual data associated with the software to determine sentiment, which is then used to rank versions. The ranking helps users and developers identify the most stable, well-received, or actively maintained versions. The sentiment analysis may involve natural language processing to extract positive, negative, or neutral sentiments from sources like issue trackers, forums, or code repositories. The ranking can be adjusted based on the volume and recency of feedback, ensuring that the most relevant and impactful versions are prioritized. This approach provides an objective, data-driven way to assess software quality without relying solely on manual reviews or subjective opinions. The method can be integrated into software repositories or development platforms to assist users in selecting the best version for their needs.
7. The method of claim 1 , further comprising generating the ranking of the version of the open source software program based on the time trend analysis.
The invention relates to ranking versions of open source software programs based on time trend analysis. Open source software often has multiple versions, and users need a way to evaluate which versions are most reliable, stable, or widely adopted over time. The method addresses this by analyzing historical data to determine trends in version usage, updates, or other relevant metrics. This helps users identify the most suitable version for their needs. The method involves collecting data on software versions, such as release dates, update frequencies, user adoption rates, or bug reports. Time trend analysis is then applied to this data to identify patterns, such as increasing or decreasing popularity, stability improvements, or declining support. The ranking is generated based on these trends, providing users with an objective assessment of version quality and relevance. Additionally, the method may incorporate other factors, such as community activity, developer contributions, or security updates, to refine the ranking. By leveraging time-based trends, the system ensures that the ranking reflects real-world usage and evolution of the software, helping users make informed decisions when selecting a version. This approach is particularly useful for developers, system administrators, and organizations that rely on open source software for critical applications.
8. A system, comprising: a hardware processor; and a memory device accessible to the hardware processor, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations including: querying a data source to retrieve electronic data describing a version of an open source software program; generating an open source stability index based on the electronic data describing the version of the open source software program, wherein the open source stability changes based on a number of issues closed and based on a number of new issues raised in the version of the open source software program; performing a time trend analysis based on the electronic data describing the version of the open source software program, wherein the time trend analysis includes determining how often in time the version of the open source software program was updated and determining how much time was needed to get a stable version of the open source software program based on no issues remaining in the version of the open source software program; generating an open source security index based on the electronic data describing the version of the open source software program; and generating a ranking of the version of the open source software program based on the open source stability index and on the open source security index.
The system evaluates and ranks versions of open source software programs by analyzing their stability and security. The system retrieves electronic data describing a specific version of an open source software program from a data source. Using this data, it calculates an open source stability index, which reflects the number of issues closed and the number of new issues raised in that version. The system also performs a time trend analysis to assess how frequently the version was updated and how long it took to achieve stability, defined as having no remaining issues. Additionally, the system generates an open source security index based on the retrieved data. The stability and security indices are then used to rank the version of the software. This approach helps users identify the most reliable and secure versions of open source software by quantifying key performance metrics. The system automates the evaluation process, providing objective rankings to guide software selection and maintenance decisions.
9. The system of claim 8 , wherein the operations further include assigning a numerical value to the open source stability index.
The system evaluates the stability of open-source software projects by analyzing factors such as code quality, community activity, and maintenance practices. It generates an open-source stability index to quantify the reliability and long-term viability of a project. The system assigns a numerical value to this index, providing a standardized metric for assessing project stability. This numerical value allows users to compare different open-source projects objectively, aiding in decision-making for software adoption, integration, or investment. The system may also track changes in the stability index over time, helping users monitor project health and identify trends. By quantifying stability, the system addresses the challenge of evaluating open-source software quality, which is often subjective and lacks standardized metrics. This enables developers, organizations, and investors to make informed choices based on data-driven assessments rather than anecdotal evidence. The numerical value can be used in automated workflows, such as dependency management tools, to enforce stability thresholds or prioritize maintenance efforts. The system may also integrate with existing software development platforms to provide real-time stability insights.
10. The system of claim 8 , wherein the operations further include assigning a numerical value to the open source security index.
The system relates to assessing and quantifying security risks associated with open-source software components. Many software projects rely on open-source libraries, but these can introduce vulnerabilities if not properly managed. The system evaluates the security posture of open-source dependencies by analyzing factors such as known vulnerabilities, patch availability, and community activity. It generates a security index that reflects the overall risk level of the open-source components in use. This index helps developers and organizations prioritize remediation efforts and make informed decisions about software dependencies. The system also assigns a numerical value to the open-source security index, allowing for standardized comparisons and thresholds to be established. This numerical representation enables automated risk assessment workflows, compliance checks, and integration with development pipelines. By providing a clear, quantifiable measure of security risk, the system helps mitigate vulnerabilities in software supply chains.
11. The system of claim 8 , wherein the operations further include keyword matching the electronic data to the version of the open source software program.
The system is designed for analyzing electronic data to detect potential unauthorized use of open source software. The core functionality involves comparing electronic data against a database of open source software versions to identify matches. This system addresses the challenge of tracking and verifying compliance with open source licensing terms, which often require attribution or other conditions when software is incorporated into proprietary systems. The system includes a database storing multiple versions of open source software programs, each associated with metadata such as version numbers, licensing terms, and other identifiers. When electronic data is submitted for analysis, the system performs keyword matching to compare the data against the stored versions. This matching process identifies similarities between the submitted data and the open source software, helping to determine whether the data contains unauthorized or improperly attributed open source code. The system may also include a user interface for submitting electronic data, viewing analysis results, and managing the database of open source software versions. The keyword matching process ensures that even minor variations in code structure or formatting do not prevent detection of potential open source usage. This approach helps organizations maintain compliance with open source licensing requirements while reducing the risk of legal disputes or penalties.
12. The system of claim 8 , wherein the operations further include performing a software sentiment analysis based on the electronic data describing the version of the open source software program.
The system analyzes electronic data describing a version of an open source software program to perform software sentiment analysis. This involves evaluating the data to determine user opinions, feedback, or perceptions about the software. The system may process various types of electronic data, such as user reviews, comments, issue reports, or other textual information related to the software. The sentiment analysis identifies positive, negative, or neutral sentiments expressed in the data, helping developers or stakeholders understand user satisfaction, common complaints, or areas for improvement. The analysis may use natural language processing techniques to extract and categorize sentiment from the text. The system may also integrate with other software development tools or platforms to provide actionable insights based on the sentiment analysis results. This helps in tracking software quality, user experience, and community engagement over time. The system may further support automated reporting or visualization of sentiment trends to assist in decision-making. The analysis can be applied to different versions of the software to compare user reactions across releases.
13. The system of claim 12 , wherein the operations further include generating the ranking of the version of the open source software program based on the software sentiment analysis.
The system is designed for evaluating and ranking open source software programs based on user sentiment analysis. The technology addresses the challenge of assessing the quality, reliability, and community perception of open source software, which is often difficult to determine from technical specifications alone. The system analyzes user feedback, discussions, and other community-generated content to derive sentiment scores, which reflect the overall perception of the software. These sentiment scores are then used to generate a ranking of different versions of the software, helping users and developers identify the most favorable or widely accepted versions. The system may also integrate additional factors, such as code quality metrics or security assessments, to refine the ranking. By leveraging sentiment analysis, the system provides a data-driven approach to evaluating open source software, reducing reliance on subjective opinions and improving decision-making for software selection and adoption. The ranking can be displayed to users, allowing them to compare versions and make informed choices based on community sentiment.
14. The system of claim 1 , wherein the operations further include generating the ranking of the version of the open source software program based on the time trend analysis.
The system relates to ranking open source software programs based on time trend analysis. The problem addressed is the difficulty in evaluating the quality, popularity, or relevance of open source software versions over time, which is crucial for developers and organizations selecting or maintaining software. The system analyzes historical data, such as usage metrics, contributions, or updates, to generate a ranking that reflects the evolution of a software program's performance or adoption. This ranking helps users identify the most reliable or actively maintained versions. The system may also incorporate additional factors, such as community engagement or bug resolution rates, to refine the ranking. By providing a time-based assessment, the system enables more informed decision-making in software selection and maintenance. The ranking is dynamically updated as new data becomes available, ensuring relevance. This approach improves transparency and efficiency in evaluating open source software, particularly in environments where version selection impacts system stability or security.
15. A memory device storing instructions that when executed cause a hardware processor to perform operations, the operations comprising: querying a data source to retrieve electronic data describing a version of an open source software program; generating an open source stability index based on the electronic data describing the version, wherein the open source stability changes based on a number of issues closed and based on a number of new issues raised in the version of the open source software program; performing a time trend analysis based on the electronic data describing the version of the open source software program, wherein the time trend analysis includes determining how often in time the version of the open source software program was updated and determining how much time was needed to get a stable version of the open source software program based on no issues remaining in the version of the open source software program; generating an open source security index based on the electronic data describing the version; and generating a ranking of the version of the open source software program based on the open source stability index and on the open source security index.
The invention relates to evaluating and ranking open source software programs based on stability and security metrics. The system analyzes electronic data describing a version of an open source software program to assess its reliability and security. The stability index is calculated by considering the number of issues closed and new issues raised in the version, reflecting how well the software handles bugs and improvements. A time trend analysis is performed to determine update frequency and the time required to achieve stability, where stability is defined by the absence of unresolved issues. The security index is generated based on security-related data in the version. The system then ranks the software version by combining the stability and security indices, providing a quantitative measure of its overall quality. This approach helps users and organizations assess the reliability and security of open source software before adoption, reducing risks associated with unstable or vulnerable versions. The invention automates the evaluation process, leveraging historical data to predict future performance and stability trends.
16. The memory device of claim 15 , wherein the operations further include performing a software sentiment analysis based on the electronic data describing the version of the open source software program.
This invention relates to memory devices configured to analyze open source software programs. The problem addressed is the need to efficiently assess and manage open source software versions by leveraging electronic data stored in memory. The memory device includes a storage medium that holds electronic data describing a version of an open source software program, such as metadata, source code, or usage statistics. The device performs operations to process this data, including executing a software sentiment analysis to evaluate the version's quality, popularity, or community perception. The analysis may involve natural language processing of user reviews, developer comments, or issue tracker entries to derive sentiment scores or trends. This helps users or automated systems make informed decisions about software adoption, updates, or maintenance. The memory device may also compare different versions of the software based on the analysis results, enabling version selection or migration recommendations. The invention improves software management by integrating sentiment analysis directly into memory-based operations, reducing reliance on external tools and enhancing decision-making efficiency.
17. The memory device of claim 16 , wherein the operations further include generating the ranking of the version of the open source software program based on the software sentiment analysis.
The invention relates to a memory device configured to analyze and rank open-source software programs based on software sentiment analysis. The device stores data related to open-source software programs, including version information, user feedback, and sentiment analysis results. The system processes this data to generate a ranking of software versions by evaluating sentiment expressed in user feedback, such as reviews, comments, or issue reports. The ranking helps users identify the most reliable or preferred versions of open-source software programs. The memory device may also store historical data on software versions, allowing for trend analysis and comparison of sentiment over time. The system can further integrate additional metrics, such as bug reports or feature requests, to refine the ranking. The invention aims to improve decision-making for users and developers by providing a data-driven assessment of software quality and user satisfaction. The memory device may be part of a larger system that includes processing units for executing sentiment analysis algorithms and databases for storing the analyzed data. The ranking can be updated dynamically as new feedback is collected and processed.
18. The memory device of claim 16 , wherein the operations further include: generating the ranking of the version of the open source software program based on the time trend analysis.
The invention relates to memory devices used in software version management systems, particularly for ranking versions of open source software programs. The problem addressed is the need to efficiently rank software versions based on their relevance or quality over time, which is crucial for developers and users selecting the most suitable version. The memory device stores a software version management system that performs operations to analyze and rank versions of open source software programs. These operations include collecting data on software versions, such as usage metrics, bug reports, and developer activity, and performing a time trend analysis to assess how these metrics evolve over time. The ranking is then generated based on this analysis, allowing users to identify the most stable, actively maintained, or otherwise preferred versions. The system may also compare different versions of the software to determine which has the highest ranking based on the time trend analysis. This helps users make informed decisions when selecting a version for deployment or further development. The memory device ensures that the ranking process is efficient and scalable, handling large datasets to provide accurate and up-to-date rankings. The invention improves software version selection by leveraging historical data trends to highlight the most reliable or actively developed versions.
Unknown
January 19, 2021
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